Personality, cognitive skills and life outcomes: evidence from the Polish follow-up study to PIAAC

Palczyńska and Świst Large-scale Assess Educ
Personality, cognitive skills and life outcomes: evidence from the Polish follow‑up study to PIAAC
Marta Palczyńska
Karolina Świst
Background: There is a growing literature providing evidence on the importance of non-cognitive skills for life outcomes. However, to date there is limited evidence on the gains from incorporating such measures into large-scale competence surveys. Methods: We investigate the relationship between personality traits and eight important life outcomes: educational attainment, labour market participation, employability, wages, job satisfaction, health, trust and life satisfaction measured in the Polish followup study to PIAAC. The study assesses two short scales: the Big Five Inventory and Grit. First, we compare explanatory power of personality traits to that of cognitive skills measured by PIAAC. Second, an incremental validity of Grit after controlling for the Big Five dimensions is assessed. Results: The analyses show that differences in personality traits are important in explaining differences in life outcomes. Educational attainment is more strongly related to cognitive skills, while for wages, the explanatory power of personality and cognitive skills is similar. For most of the subjective outcomes, the Big Five traits outperform cognitive skills in predictive power. Conscientiousness is positively related to most of the outcomes analysed while Neuroticism has a negative relationship. After controlling for sociodemographic characteristics and cognitive skills, Big Five traits add explanatory power to all models except for employability. Grit explains some additional variation in educational attainment and in a number of subjective outcomes: health, trust, job and life satisfaction, even after adjusting for the effects of cognitive skills and Big Five traits. Conclusions: Given the potential benefits and relatively small burden on respondents in terms of required time it seems advisable to incorporate measures of personality traits into competence surveys as they contribute to explaining the variability in policyrelevant outcomes. The use of the Big Five Inventory seems preferable to Grit when a broad range of life outcomes is of interest, as the former covers multiple aspects of personality. However, using both scales offers an improvement in explanatory power.
PIAAC; Cognitive skills; Personality; Grit; Earnings; Health; Well-being; Perseverance of effort; Consistency of interest
Background
There is a consensus that cognitive skills have important effects on economic and social
outcomes. The evidence is ample, both in national and cross-national data. For over two
decades comparable international surveys on cognitive skills have been conducted,1 the
most recent being the Programme for the International Assessment of Adult
Competencies (PIAAC) coordinated by the OECD. The programme confirmed the importance of
cognitive skills for economic and social outcomes in the participating countries
(da
Costa et al. 2014; OECD 2013a; OECD 2016)
.
However, it has also been recognised that cognitive skills as measured by achievement
tests are not the only determinants of a successful life. There is a growing literature
providing evidence on the importance of non-cognitive skills for life outcomes
(for reviews,
see Almlund et al. 2011; Borghans et al. 2008)
.
The striking causal evidence on the predictive power of non-cognitive skills has come
from the Perry Preschool Program. This experimental intervention, targeted at
disadvantaged 3-year-old children, included weekly home visits to enrich children–parent
interactions and preschool education with a curriculum aimed at fostering children’s
cognitive and socio-emotional skills. The programme lasted 2 years and both treatment
and control groups were followed through to age 40
(Heckman et al. 2010a)
. The
programme did not boost IQ in the long run but did produce significant treatment effects
for educational and economic outcomes and crime
(Heckman et al. 2010b)
.
Heckman
et al. (2013
) show that, to a large extent, the effectiveness of the programme can actually
be attributed to persistent changes in non-cognitive skills.
The general educational development (GED) programme in the USA provides further
evidence of the importance of non-cognitive skills for educational and economic
outcomes. This programme offers high school dropouts the possibility to formally certify
that their cognitive skills are equivalent to those of high school graduates. Despite the
fact that their cognitive skills are similar, they nevertheless perform worse in the labour
market than high school graduates without further college education.
Heckman and
Kautz (2012)
show that the non-cognitive skills of GED recipients are closer to high
school dropouts than to graduates, which results in the differences in the labour market
performance.
Although it is difficult to draw a sharp line between cognitive and non-cognitive skills
(Almlund et al. 2011)
, the term “non-cognitive skills” is used by economists for a wide
range of traits which are believed to be distinct from skills measured by IQ tests and
achievement tests, such as personality, motivation or interests. Special attention has
been paid to the concept of personality. One of the most widely used frameworks for
describing human personality is the Big Five model. It identifies five dimensions of
personality: Openness to experience, Conscientiousness, Extraversion, Agreeableness, and
Neuroticism
(Costa and McCrae 1985; John and Srivastava 1999; McCrae and Costa
1999)
.
A large volume of empirical literature studies the predictive power of
personality traits. These studies show that personality, and especially traits connected to
1 These included studies on school-aged children: PISA, TIMSS, PIRLS; and on the adult population: IALS, ALL,
PIAAC.
Conscientiousness and Neuroticism, predicts a wide range of important life outcomes.
Conscientiousness is positively related to job performance, training proficiency and
personnel data (such as salary or promotions), while Openness and Extraversion predict
training proficiency
(Barrick and Mount 1991)
. Various studies have shown that there is
a wage penalty for Agreeableness and Neuroticism
(Mueller and Plug 2006; Nyhus and
Pons 2005; O’Connell and Sheikh 2011)
. Studies on US samples note a positive
association between Openness and wages
(Mueller and Plug 2006; O’Connell and Sheikh 2011)
.
The importance of the traits relating to Neuroticism/Emotional stability, such as
selfesteem and locus of control, for the wage setting has been confirmed by Drago (2011)
and
Heineck and Anger (2010)
. Educational attainment is best predicted by Openness
to Experience
(Goldberg et al. 1998; O’Connell and Sheikh 2011; Van Eijck and de Graaf
2004)
. The first two studies also report a positive but much weaker association of
Conscientiousness with years of education. Openness to Experience, also called Intellect, has
facets of Ideas and Fantasy which are often related to measured intelligence
(Almlund
et al. 2011)
.
Hampson et al. (2007
) find that Extraversion, Agreeableness and
Conscientiousness, measured during childhood, predict self-rated health and healthy
behaviours in midlife. Part of this effect is indirect through educational attainment. The same
traits have positive effects on longevity
(Roberts et al. 2007)
. The latter meta-analysis
also shows that all personality traits are stronger predictors of mortality than
socio-economic status and are comparable to IQ. Overall, among the Big Five traits,
Conscientiousness is the strongest predictor of health outcomes. The evidence on the relationship
between personality and generalised trust is mixed. Only the result on the positive link
between Agreeableness and trust emerges consistently between many studies
(Anderson
2010; Dohmen et al. 2008; Freitag and Bauer 2016)
. Additionally, some studies find that
Openness is also positively related to trust
(Dohmen et al. 2008; Freitag and Bauer 2016)
.
Dohmen et al. (2008) show that Neuroticism and Conscientiousness are negatively
linked to trust. By contrast, Freitag and Bauer (2016) find that Conscientiousness relates
positively to trust. Personality can also explain individual differences in life satisfaction.
A meta-analysis indicates that Neuroticism and Extraversion are the strongest
predictors of subjective well-being among the Big Five traits
(DeNeve and Cooper 1998)
. More
recently, using the British Cohort Study 1970,
Prevoo and Ter Weel (2015
) show that
Extraversion in childhood is the strongest predictor of life satisfaction around 30 years
later, while Neuroticism does not have a significant influence. When analysing workers’
well-being, a meta-analysis by
Judge et al. (2002
) indicates that extraverts are more likely
to be satisfied with their work, while neurotic individuals are less likely to be satisfied.
Using German PIAAC longitudinal data, Rammstedt et al. (2017) show that after
controlling competences, Big Five traits incrementally predict life satisfaction and health,
and to a lesser extent income, educational attainment and employability.
In sum, Big Five traits play an important role in predicting a wide range of economic
and social outcomes. While most of the literature examines the effect in the United
States and Western Europe, the study by Cunningham et al. (2016) is an exception.
Using the Peruvian National Skills and Labor Market Survey, they find that Openness
and Emotional Stability are related to wages, and that an aggregate of these
two—plasticity—is related to employment. There is also a negative link between traits connected
to Agreeableness and wages. Additionally, the study includes one of the Grit subscales:
Perseverance of effort. They show that it is positively correlated with employment when
controlling for Conscientiousness.
Although the Big Five taxonomy is probably the most widely used personality
framework, new research on personality traits is emerging nowadays. The trait termed Grit
deserves special attention, as a relatively new construct that quickly attracted attention
and started to be collected in international surveys such as the Skills Towards
Employment and Productivity (STEP) and was even included in the 2017 edition of the National
Assessment of Educational Progress (NAEP) in the US
(Bertling 2016)
. It is not part of
the Big Five model but can be related to it. Grit is defined as perseverance and passion
for long-term goals. People with a high Grit level sustain their interest and effort in an
activity, despite challenges, failures and a lack of positive feedback
(Duckworth et al.
2007; Duckworth and Quinn 2009)
. Grit is a similar construct to one of the Big Five
factors—Conscientiousness—which is defined as a “socially prescribed impulse control
that facilitates task- and goal-related behaviour” (John and Srivastava 1999). It consists
of such traits as being careful, thorough, responsible and organised. Additionally, and
just like Grit, it includes volitional traits such as being hardworking,
achievement-oriented and persevering
(Barrick and Mount 1991)
. However, it is argued that Grit and
Conscientiousness are conceptually different as Grit emphasises stamina: being able to
sustain effort and interest in projects which take a lot of time to complete
(Duckworth
et al. 2007)
. Nevertheless, both constructs correlate strongly. The results vary from 0.44
(Ivcevic and Brackett 2014)
to 0.64 and 0.74 for the Consistency of interest and
Perseverance of effort subscales respectively
(Duckworth and Quinn 2009)
. A twin study by
Rimfeld et al. (2016
) shows that Grit is similar to other psychological traits (for example
Big Five traits) in its nature—it shows genetic influence (heritability of Perseverance of
effort = 37% and of Consistency of interest = 20%) and no shared environmental
influence. They conclude that perseverance of effort and Conscientiousness are both
phenotypically and genetically correlated.
Although Grit has a much shorter tradition than the Big Five model, the body of
evidence on its predictive power is growing. The largest body of literature concerns the
relationship between the level of Grit and educational attainment. Eskreis-Winkler
et al. (2014) show that grittier individuals are more likely to graduate from high school,
and that the relationship holds also when controlling for academic Conscientiousness.
Moreover, individuals with a higher level of Grit have smaller chances of dropping out
of education or the labour market (becoming NEETs—not in education, employment or
training) at age 18–20
(Mendolia and Walker 2014)
. According to
Duckworth and Quinn
(2009)
, children with a high Grit level are more likely to win in spelling competitions and
grittier adolescents obtain higher GPAs (Grade Point Average). However,
Bazelais et al.
(2016
) analysed a sample of college students to find that Grit is an insignificant
predictor of academic achievement, when controlled for the prior academic performance. A
recent meta-analysis by
Credé et al. (2017
) finds that Grit is related to academic
performance and retention but its facets differ in terms of the strength of this relationship: the
Perseverance of effort facet is related more strongly to all academic performance criteria
than the Consistency of interest facet.
Grittier individuals also tend to have more stable life outcomes: they make less career
changes (when controlled for other personality traits and age), drop out less frequently
during training, and have longer-lasting marriages
(Eskreis-Winkler et al. 2014;
Duckworth and Quinn 2009)
. The positive effect of Grit on academic and labour performance
exists both in individualistic and collective cultures
(Datu et al. 2016; Suzuki et al. 2015)
.
Although most of the researchers focus on the positive influence of Grit,
Lucas et al.
(2015
) show in their experiment that too much Grit can be harmful. Grittier participants
are less likely to quit activities even when they fail or the activities cost them too much.
There is mixed empirical evidence on the incremental validity of Grit. When
controlling for Conscientiousness and the other Big Five traits,
Duckworth and Quinn (2009)
find that grittier individuals attain higher levels of education than other individuals of
the same age. However,
Dumfart and Neubauer (2016)
find no incremental contribution
of Grit when analysing the combined impact of intelligence and Conscientiousness on
secondary school achievement (measured by GPA, science and languages).
Rimfeld et al.
(2016
), in their twin study, find that personality traits (mainly Conscientiousness)
predict about 6% of variance in GCSE (General Certificate of Secondary Education) grades
but Grit incremental validity is low.
Credé et al. (2017
) find that overall Grit does not
explain additional variance in academic performance (measured by GPAs in high school,
college, and individual grades) after controlling for Conscientiousness, but that
Perseverance of effort facet explains a substantial incremental variance in all three measures
of academic performance even after controlling for Conscientiousness. Their results
suggest that the two Grit facets should be analysed separately.
Almlund et al. (2011) summarise why personality should not be ignored in the
research of life outcomes. First, personality traits have comparable predictive power for
important outcomes to measures of cognition. Moreover, very often performance in
achievement tests depends not only on cognition but also on personality. The authors
also highlight the relevance of personality traits for policy interventions, as these traits
are more malleable than cognition; hence interventions aimed at boosting non-cognitive
skills can be a way of addressing social problems.
Culture may influence personality-outcome relationships. As
Henrich et al. (2010
)
argue, the results of Western empirical studies can be generalised to other contexts only
with great caution. One of the established dimensions of culture is
individualism/collectivism
(Hofstede 1980)
. In the individualistic context, there is an emphasis on
personal autonomy and self-fulfilment, whereas collectivist cultures attach more value to
interpersonal harmony and common group goals
(Inglehart 2006)
. There is some
evidence that collectivist culture moderates the personality-economic outcomes
relationship
(Grijalva and Newman 2015)
. Further, Datu et al. (2016) argue that the Consistency
of interest facet of Grit is less relevant in collectivist cultures. On the other hand, a few
studies on personality-economic outcomes relationships in collectivist cultures have
replicated earlier results from the US and Western Europe
(Cunningham et al. 2016;
Suzuki et al. 2015)
. More research in diverse cultural contexts is needed to assess the
impact of culture on the relationships under investigation.
One of the challenges in personality assessment in large-scale studies is the
measurement of personality traits. Unlike standardised achievement tests, personality tests are
based on self-reported measures, which are less objective. The only international
survey that collects information, both on cognitive and non-cognitive skills, is the STEP
study conducted in developing countries. The preliminary findings show that more
conscientious, emotionally stable and grittier (determined) workers find their first job
faster. Likewise, non-cognitive skills are associated with higher wages
(World Bank
2014)
.
However, we still lack an international study that systematically evaluates the
combined impact of cognitive and non-cognitive skills in developed countries. While the
first cycle of PIAAC made an assessment across three domains—literacy, numeracy
and problem solving in technology-rich environments—no non-cognitive measures are
available. The second cycle of PIAAC is planned for 2018–2023 and will be an
opportunity to build on experience from the previous cycle. One of the possible changes might
be to include new areas of assessment, particularly non-cognitive skills.
The objective of this paper is to assess the analytical importance of personality
measures compared to competences measured in PIAAC and to compare the criterion
validity of the Big Five and Grit constructs in a large representative sample of adults
in Poland. In a related study, Rammstedt et al. (2017) used the data from the German
PIAAC longitudinal study to assess the predictive power of Big Five traits. They show
that, after accounting for competencies, personality explains incremental variance in
educational attainment, employment status, income, life satisfaction, and health. In our
article, we extend this research by comparing criterion validity of the two popular scales:
Big Five and Grit, also taking into account the additional life outcomes of labour force
participation and job satisfaction. Moreover, we investigate the incremental validity of
Grit after adjusting for Big Five dimensions. To the best of our knowledge, this is the first
article to provide evidence on the relationship between personality and important life
outcomes in the Polish adult population.
The paper is organised as follows. In the next section, we describe the data set and the
measures used. We then investigate the relationship between cognitive and
non-cognitive skills and life outcomes. This is followed by the discussion of the incremental
validity of Grit. The last section concludes.
Methods
Research design and sample
We analyse the data from the Polish Follow-up Study to the Programme for International
Assessment of Adult Competencies (postPIAAC). The main goals of the study were to
gather longitudinal information on PIAAC respondents in Poland and to collect
additional background information not available in the international study. The background
questionnaire (BQ) of postPIAAC is based on the PIAAC international questionnaire
with many additional questions and some modifications. The methodology of
collecting labour market outcomes was not changed. Regarding other outcomes, a question on
life satisfaction was added and the question on political efficacy was removed, leaving
the rest of the social indicators unchanged (health and trust). The BQ was administered
as a computer-assisted personal interview (CAPI). The study included parts with direct
assessment, both on computer (a working memory test and a basic ICT skills test) and
on paper (a coding speed test, a Big Five personality test and a self-assessment of skills).
The Grit test was part of the BQ. The analysis is based on postPIAAC data combined
with the proficiency estimates from PIAAC. The interval between the interviews for an
individual respondent is from 2.5 to 3.5 years. The analysis thus assumes that
respondents’ cognitive skills have not changed significantly between the two waves.
The target population for PIAAC included all non-institutionalised individuals aged
16–65, residing in Poland during the period of data collection in 2011–2012. The
target population of postPIAAC were PIAAC respondents who lived in Poland during the
fieldwork conducted between October 2014 and February 2015 (aged 18–69 at that
time). PIAAC respondents who had either died or emigrated between the interviewers’
visits were classified as ineligible in postPIAAC. The weighting process of the
postPIAAC sample was based on PIAAC guidelines
(OECD 2013b)
. The final weight in PIAAC
was taken as the person base weight in postPIAAC. The next step involved correcting
for non-response in order to reduce potential bias arising from differences between
respondents and non-respondents. Using a classification tree methodology, adjustment
cells were constructed which were homogeneous with respect to the response rate. The
calibration referred to the population estimates produced by PIAAC with respect to age,
gender and proficiency score. The weighting process ensured that the average PIAAC
results are replicated between the original and postPIAAC sample with regard to
standard characteristics such as gender, age or educational attainment. Additionally,
replication weights (paired jackknife) were computed in order to facilitate the estimation of
variance.
Of the initial 9366 respondents in PIAAC, 5224 completed postPIAAC interviews in
2014/2015. After selecting individuals with valid answers to the relevant outcome
questions, we kept a working sample of 4454 for the analysis of life outcomes. The working
sample for job quality outcomes was further reduced to 2507 and 2059 respectively for
job satisfaction and wages (only dependent workers).
Measures
Personality
The study includes two self-reporting scales: the Big Five Inventory-Short (BFI-S)
(Gerlitz and Schupp 2005; John et al. 1991)
and the short eight-item Grit scale (Grit-S)
(Duckworth and Quinn 2009). BFI-S includes 3 items per dimension with answers on a
seven-point Likert type scale (1—“disagree completely” to 7—“agree completely”). Grit
scale is answered on a five-point scale ranging from 1—“not like me at all” to 5—“very
much like me”.
Palczyńska and Świst (2016
) perform an item-level analysis of BFI-S and
Grit-S scales using both Classical Test Theory and Item Response Theory techniques.
They show that most of the Big Five items discriminate well between people possessing a
high and a low level of a given trait, though the reverse-worded items perform weaker.
The reliability of scales is moderate but satisfactory given their length (three items per
each subscale) and improves after removing problematic items.2 All Grit items, except
one, function well psychometrically and its subscales have comparable reliability
(standardised Cronbach’s alpha values 0.65–0.67).
2 The standardised Cronbach’s alpha values range from 0.36 for Extraversion to 0.61 for Conscientiousness and after
removing negative items they range from 0.45 for Agreeableness to 0.66 for Conscientiousness.
The BFI-S theoretical five-factor structure was not replicated in the Polish adult
population sample.3 However, literature suggests that reverse-worded items form a separate
factor
(DiStefano and Motl 2006)
. A six-factor oblique model with an additional factor
loading reverse-worded items provides satisfactory fit with the data (RMSEA = 0.077,
TLI = 0.860, CFI = 0.905). In case of Grit-S, the second-order theoretical structure does
not hold in our sample as it is not identified. A two-factor model supported by the recent
literature (
Credé et al. 2017
;
Midkiff et al. 2017
) provides good fit with the data (RMSEA:
0.059, CFI: 0.964, TLI: 0.947). We use factor score from the six-factor oblique model for
Big Five and from the two-factor model for Grit-S in multivariate analyses presented in
the paper. We generated factor scores using the regression method for both scales. As
researchers have often used Grit-S as a single factor
(Duckworth et al. 2011;
EskreisWinkler et al. 2014)
, and computing overall Grit from all the items is recommended by
Duckworth et al. (2007), we also compare our results from the two-factor model to the
unidimensional model. However, one has to note that the unidimensional model has
poorer fit to the data (RMSEA: 0.135, CFI: 0.804, TLI: 0.726).
The scores for BFI-S and Grit-S subscales are standardised with a mean of zero and a
standard deviation of one.
Cognitive skills
PIAAC measures basic information processing skills: literacy and numeracy. They
represent acquired knowledge, sometimes called crystallized intelligence. Literacy is defined
as “the ability to understand, evaluate, use and engage with written texts to participate in
society, to achieve one’s goals, and to develop one’s knowledge and potential”
(OECD
2013a)
. Numeracy refers to “the ability to access, use, interpret and communicate
mathematical information and ideas in order to engage in and manage the mathematical
demands of a range of situations in adult life.”
(OECD 2013a)
Both skill domains are
measured on a 500-point scale. For analytical purposes, we standardise scores in the
subsequent analyses to have a mean of zero and a standard deviation of one. Although
intended to measure different skills, PIAAC literacy and numeracy scales are strongly
correlated (0.85 in our sample). The subsequent analyses use numeracy measure but the
results for literacy are not qualitatively different.4
PIAAC uses multiple imputations (plausible values—PVs) to increase the accuracy of
the cognitive measures
(for details see OECD 2013b)
. Ten PVs are drawn for each
respondent per domain. We ran all the regression analyses separately for each of the ten
PVs and report the average results with the imputation error added to the variance
estimator.5
Life outcomes
The present study analyses eight important life outcomes: educational attainment,
labour force participation, employability, wages, job satisfaction, health, trust and life
3 The five-factor orthogonal model yields the following fit statistics: RMSEA= 0.199, TLI = 0.450, CFI = 0.542,
whereas the five-factor oblique model: RMSEA= 0.127, TLI = 0.625, CFI = 0.725.
4 Results for literacy are presented in Additional file 1.
5 Stata command repest is used.
satisfaction measured in postPIAAC. For each outcome we provide the analogous
variable from PIAAC in brackets.
Educational attainment: Educational attainment was measured in years based on the
highest level of education reported by the respondent [B_Q01aPL].
Labour force status: Labour force status was assessed using a series of questions based
on ILO (International Labour Organization) methodology. Labour force participation
means being active on the labour market (employed or unemployed). Employability was
assessed among active individuals [C_D05].
Wages: Respondents were allowed to report wages for different time intervals. The
answers were recalculated into hourly wages based on hours worked per week. This
outcome is analysed among dependent workers. Logarithm of wages is used throughout the
analysis [EARNHR].
Job satisfaction: Respondents assessed their job satisfaction on a five-point scale from
“extremely satisfied” to “extremely dissatisfied” [D_Q14].
Health: Respondents rated their general health on a five-point scale from “excellent” to
“poor” [I_Q08].
Trust: The indicator of trust is an average of two items on social trust: “There are only
a few people you can trust completely” and “If you are not careful, other people will take
advantage of you” [I_Q07a, I_Q07b]. The respondents could agree with the statements
on a five-point scale ranging from “strongly agree” to “strongly disagree”.
Life satisfaction: Current life satisfaction was measured with one item on a seven-point
scale ranging from “extremely satisfied” to “extremely dissatisfied” [No question on life
satisfaction in PIAAC].
Descriptive statistics of life outcomes can be found in Table 9 in Appendix.
Categories of ordinal variables with a frequency below 5% were merged with the neighbouring
category.
Control variables
In all the analyses, besides the main variables of interest: personality and cognitive skills,
we included controls for demographic and socio-economic characteristics. Specifically,
we controlled for age, age squared, gender and years of education.6 For some of the
outcomes, additional controls were included. In case of educational attainment we included
father’s education and mother’s education in the model, in the analysis of social
outcomes we added employment status and in the analysis of labour market outcomes the
occupation (using 9 groups from ISCO classification). Army workers (ISCO = 0) were
excluded from the analysis.
Methods
We used ordinary least squares regression to analyse all the outcomes as comparability
over models is very important for the purposes of this study. First, this approach allows
us to compare the effect estimates between analyses of different outcomes. Second, it
overcomes the problem of incomparable coefficients in models with different
6 Except for the analysis of educational attainment.
independent variables
(Mood 2010)
. We performed sensitivity analyses using non-linear
models when appropriate and the results are qualitatively similar to the linear models in
terms of the sign and the significance of the relationship between non-cognitive skills
and life outcomes.7
To assess the incremental validity of Grit after controlling for the Big Five we compare
nested specifications checking whether Perseverance of effort and Consistency of
interest explain incremental variance and whether the relationship of Big Five traits with the
outcomes changes after adjusting for Grit subscales.
The complex survey design and sampling weights have been accounted for in the
estimations of the parameters in the regression analysis.
Results
In order to investigate the relationships between the personality scales and the outcomes
and compare them to the impact of cognitive skills we estimate seven models for each
outcome. The first one includes control variables only and serves as a benchmark. The
next three specifications separately consider the associations between the outcome and
numeracy, Big Five and Grit. Specifications 5 and 6 include numeracy and Big Five or
Grit respectively, while the last column shows the incremental validity of Grit when
controls are included for numeracy and the Big Five. The first part of this section focuses on
specifications 1–6 while the results on the incremental value of Grit for the prediction of
life outcomes are covered in a separate subsection.
Educational attainment
The variance explained by cognitive skills rivals that explained by measured personality
traits (Table 1, specifications 2–4). Including personality traits (either Big Five or Grit) in
regressions with cognitive skills explains around 1% of the additional variance
(specifications 5–6). Openness is associated with higher levels of education while Extraversion,
7 Results are presented in Additional file 2.
Agreeableness and Neuroticism are associated with lower levels of education
(specification 5). In contrast to previous studies
(e.g. Poropat 2009; Van Eijck and de Graaf 2004)
,
we do not find an association between Conscientiousness and educational attainment.
However, recent findings by Rammstedt et al. (2017) suggest that this association is
actually non-linear. An additional analysis including quadratic terms of personality traits in
the model confirms a hump-shaped association between conscientiousness and
educational attainment. Individuals with an intermediate level of conscientiousness have the
highest average educational attainment. The results for the other Big Five traits support
the linear representation of their relationship with education. Only the Consistency of
interest facet of Grit is positively correlated with years of education and its effect is half
of the size of the effect of Openness, which is the strongest predictor among Big Five
traits (β = 0.07 and β = 0.14 respectively).
It has to be stressed that personality traits and cognitive skills are measured at the
same point in time for the entire sample. This means that older individuals finished their
formal education many years previously while the young are often still in education.
Therefore, we can only examine whether personality helps to explain individual variation
in educational attainment measured by completed years of schooling, which is a
censored measure for the younger cohorts.
As socio-economic status (SES) is believed to be one of the main determinants of
educational attainment
(Van Eijck and de Graaf 2004)
, we include controls for parental
education to account for it. To provide results comparable to earlier research, appendix
reports the results of the analysis without controlling for SES (Table 10). The
standardised effects of Big Five traits are around 1.5 times higher than in the model presented
below.
Labour market outcomes
Several studies suggest that personality traits predict labour market outcomes. The
decision to participate or not in the labour market appears to be related to individual
personality traits. Controlling for education, age and gender, conscientious individuals are more
likely to be active on the labour market while agreeable and neurotic individuals are less
likely (Table 2, specification 5). The relationship between cognitive skills as measured by
PIAAC numeracy scores and labour force participation is positive but not statistically
significant. Adding Big Five traits to the model slightly increases the explained variance
by 1.4% while the effects of numeracy and Grit are much smaller (Table 2, specifications
2–4).
Among individuals active in the labour market, cognitive skills and personality traits
are unrelated to employment after controlling for basic socio-demographic factors and
explain only marginal additional variance (Table 3, specifications 2–4). This lack of a
clear association with employment can be partially explained by the differences in job
search behaviours between individuals with internal and external locus of control—a
trait linked to Neuroticism. People with internal locus of control tend to search for work
more intensively. At the same time, they have higher reservation wages
(Caliendo et al.
2015)
. Therefore, the effect on their employability is ambiguous.
The analysis uses the ILO definitions of employment and activity in the labour
market. However, there are differences between ILO employment status and the main
activity declared by respondents. The share of employed individuals is 67 and 62% while the
share of unemployed is 5 and 8%, according to the ILO definition and respondents’
declarations, respectively. To test the robustness of our findings, we report the results of
the analysis using the self-declared main activity of individuals (Tables 11, 12 in
Appendix). The relationship between personality and activity on the labour market is not
qualitatively different when the different measure of inactivity is used. When we turn
to employability the results differ slightly. The positive association between numeracy
and employment is much stronger and significant. Also conscientiousness is positively
related to employment in this specification. The source of these differences may be the
composition of the group of employed: people who work a limited number of hours
declare different activities such as education, housework or even unemployment, thus,
the group of employed becomes more homogeneous when a self-declared measure is
used.
Once a person is employed, the important question is the quality of their job. The most
frequently used indicators of job quality are wages and job satisfaction. The Big Five traits
explain only slightly more of the variation in wages than cognitive skills: 1.3% and 0.8%
respectively while Grit explains almost no additional variance (Table 4, specifications
2–4). Considering Big Five traits and cognitive skills jointly (specification 5) increases
the explained variance by 2%. Conscientious individuals are more likely to earn more. By
contrast, Agreeableness and Neuroticism are associated with lower wages. These results
are in line with empirical studies on Big Five from other countries
(e.g. Mueller and
Plug 2006; Nyhus and Pons 2005)
. In contrast to studies conducted in US
(Mueller and
Plug 2006; O’Connell and Sheikh 2011)
, Openness is not related to wages in our sample.
Additional analysis also did not replicate previous findings on a hump-shaped
relationship between openness and wages reported by Rammstedt et al. (2017). The effect sizes
of Conscientiousness and Agreeableness on wages are over two times higher than the
effect of numeracy (β = 0.23, β = 0.27, β = 0.10). Cognitive and non-cognitive skills might
affect wages indirectly via the choice of occupation. When we compare the influence of
cognitive and non-cognitive skills on wages without controlling for occupation the
difference decreases but the effects of Conscientiousness and Agreeableness are still one
and a half times higher. Neither of the facets of Grit is related to wages in our sample.
The next dimension of job quality examined is job satisfaction which is by definition
subjective. Results in Table 5 show that personality traits do better at predicting job
satisfaction than do cognitive skills. Big Five and Grit traits explain 3.2 and 2% additional
variance respectively. Conscientiousness is linked to higher job satisfaction (β = 0.23)
while Neuroticism is linked to lower job satisfaction ( β = − 0.12). Perseverance of effort
is associated with higher levels of job satisfaction (β = 0.17).
Social outcomes
In addition to examining the relationships between personality measures and
educational and labour market outcomes, it is also useful to examine their relationship with
social outcomes. Following
OECD (2007
; 2013a), interpersonal trust and health are
considered as social outcomes.
Big Five and Grit traits explain more additional variance in health than cognitive skills:
2.6, 1.5 and 0.3% respectively (Table 6, specifications 2–4). Considering Big Five traits
and cognitive skills jointly (specification 5) increases the explained variance by 2.9%. In
line with the earlier research on PIAAC
(da Costa et al. 2014; OECD 2013a)
, numeracy
* p < 0.05, ** p < 0.01, *** p < 0.001 Control variables: age, age squared, gender, years of education, 1‑ digit ISCO. ISCO = 0
excluded. Dependent variable, numeracy and non‑ cognitive skills are standardised. Full estimation results are presented in
Additional file 3: Table S5
proficiency is positively linked to health but the effect is small (β = 0.06). Lower levels
of Conscientiousness and Extraversion are associated with lower levels of health while
lower levels of Neuroticism are associated with higher levels of health. A standard
deviation increase in Perseverance of effort results in a 0.10 SD increase in health, holding all
other variables constant. Also Consistency of interest is positively associated with health
but the effect is not significant.
Also in the case of trust, Big Five and Grit traits explain more additional variance than
cognitive skills: 1.3, 0.9 and 0.7% respectively (Table 7, specifications 2–4). Considering
Big Five traits and cognitive skills jointly (specification 5) increases the explained
variance in trust by 1.9%. As in the case of health, numeracy is positively correlated with
trust and the effect is stronger (β = 0.09). Neuroticism is the only Big Five trait
associated with trust. Neurotic people are more likely to report lower levels of trust and the
absolute effect size is similar to numeracy. The results did not replicate findings on the
positive association between trust and Openness/Agreeableness and the negative
association between trust and Conscientiousness
(Dohmen et al. 2008)
. Perseverance of effort
* p < 0.05, ** p < 0.01, *** p < 0.001. Control variables: age, age squared, gender, years of education, employment status.
Dependent variable, numeracy and non‑ cognitive skills are standardised. Full estimation results are presented in Additional
file 3: Table S6
* p < 0.05, ** p < 0.01, *** p < 0.001. Control variables: age, age squared, gender, years of education, employment status.
Dependent variable, numeracy and non‑ cognitive skills are standardised. Full estimation results are presented in Additional
file 3: Table S7
is negatively associated with trust and its effect is similar to the effect of Neuroticism
(β = − 0.09).
Life satisfaction
General life satisfaction is one of the central outcomes covering different life domains.
In contrast to health and trust, life satisfaction is not related to cognitive skills.
However, the associations with personality traits are very strong. Big Five traits increase the
explained variance in life satisfaction by 5.8% while Grit does so by 5.2%. For a standard
deviation increase in Conscientiousness, life satisfaction increases by 0.27 SD, holding
all other variables constant. Also Extraversion has a positive relationship with life
satisfaction (β = 0.11), while Neuroticism has a negative one (β = − 0.13). Similar to
Conscientiousness, both facets of Grit are positively related to life satisfaction but the effect
of Perseverance of effort is much stronger than the Consistency of interest (β = 0.19 and
β = 0.07 respectively).
* p < 0.05, ** p < 0.01, *** p < 0.001. Control variables: age, age squared, gender, years of education, employment status.
Dependent variable, numeracy and non‑ cognitive skills are standardised. Full estimation results are presented in Additional
file 3: Table S8
The incremental validity of Grit
The construct of Grit is often related conceptually to the Big Five factor of
Conscientiousness and the empirical correlations between the two are high (see Introduction). An
important question, therefore, is whether Grit provides some extra information when we control
for the Big Five traits. The correlation between Grit and Conscientiousness in the
postPIAAC sample is 0.37, indicating that 14% of variation in scores across these scales is shared.
Not all associations between the outcomes and Grit subscales and Conscientiousness
follow a similar pattern (specification 7, Tables 1, 2, 3, 4, 5, 6, 7, 8). Some outcomes are related
to one of the Grit subscales but not to Conscientiousness (educational attainment and
trust), some are associated with Conscientiousness but not with Grit (labour force
participation, wages) and for some we observe similar effects (job satisfaction, health and life
satisfaction). The facets of Grit explain around 1% of additional variance in educational
attainment, job satisfaction, health and trust, even after adjusting for the effects of cognitive
skills and Big Five traits. Moreover, they explain 2.6% of additional variance in life
satisfaction. Taking into account that for some outcomes the overall variance explained in the full
model is even as low as 6% (in the case of trust), these additional effects are not negligible.8
In sum, Grit has an incremental value for some of the life outcomes examined when
adjusting for the effects of numeracy and Big Five personality traits. To date, its predictive power was
mainly validated in the context of school outcomes: attainment and grades. In this respect,
and in line with previous research
(Duckworth and Quinn 2009; Eskreis-Winkler et al. 2014)
,
Grit is significantly associated with educational attainment after controlling for Big Five traits
and explains an additional 1% of variance while Conscientiousness is not related to education.
However, this effect is driven by the Consistency of interest facet of Grit, and not Perseverance
of effort as suggested by Credé et al. (2017). Also, Grit is significantly and negatively
associated with trust and improves the model while Conscientiousness does not. Regarding health,
life satisfaction and to lesser extent job satisfaction, much of the effect of Grit in explaining
these outcomes is shared with Conscientiousness. In contrast to previous studies
(e.g.
EskreisWinkler et al. 2014; Suzuki et al. 2015)
, we do not find a positive relationship between Grit and
economic outcomes measured by labour force participation, employability and wages.
Discussion
The present study seeks to assess the analytical importance of personality measures
compared to cognitive skills measured in PIAAC and to compare the explanatory power of
the Big Five and Grit constructs in a large representative sample of adults in Poland. It
investigates the relationships between personality and a wide range of important life
outcomes, as well as the incremental validity of Grit when Big Five traits are accounted for.
Overall, the results confirm earlier findings from the literature that differences in
personality traits are important in explaining differences in life outcomes. For most of the subjective
outcomes, the Big Five traits outperform cognitive skills in predictive power. Only educational
attainment is more strongly related to cognitive skills, while for wages, the explanatory power
of personality and cognitive skills is similar. After controlling for sociodemographic
characteristics and cognitive skills, Big Five traits are incrementally predictive of all life outcomes except
8 For all the outcomes when analysing Grit as an overall score from the unidimensional model, the variance explained is
the same or slightly lower (max. ΔR2=0.004) than in the models analysing the facets of Grit from the two-factor model
(Appendix: Table 13).
for employability. The strongest effects are observed for subjective, self-declared outcomes such
as health or job satisfaction. The stronger predictive power of Big Five for subjective outcomes
confirms the results of Rammstedt et al. (2017), who argued that it is the same aggregation level
of personality measures and the subjective measures which may drive the correlation.
Moreover, these higher correlations may be due to the response style on attitudinal and self‐evaluative
items of Likert scales. Further research on this issue is needed.
The effects of particular traits are largely in agreement with predictions. They confirm
similar effects observed in previous studies conducted in the United States and Western
Europe. Conscientiousness is positively related to most of the outcomes analysed while
Neuroticism has a negative relationship. Extraverted individuals are more likely to attain
lower levels of education. They are also more satisfied with their life and job and feel
healthier. Agreeableness is associated with lower levels of education and negative labour
market outcomes. Openness is strongly and positively related to educational attainment.
In contrast to previous studies
(e.g. Mueller and Plug 2006; Rammstedt et al. 2017)
we
do not find relationship between Openness and wages.
Moving beyond the research focusing on the Big Five model, we complement the few studies
that have examined the incremental validity of Grit
(e.g. Duckworth and Quinn 2009;
EskreisWinkler et al. 2014; Suzuki et al. 2015)
and extend it across more life domains. Using a
representative sample of adults, we show that the Grit-S scale has less predictive power than the
BFI-S, but jointly considering both scales increases the explained variance in many outcomes.
The effects on many outcomes are not smaller than the effects of Big Five traits. Although
literature suggests that Grit and Conscientiousness are conceptually similar (e.g.
Credé et al. 2017
),
they share the effects on outcomes only in case of health, life satisfaction and to a lesser extent
job satisfaction. In contrast to Conscientiousness, Grit is unrelated to labour market outcomes
but explains additional variation in educational attainment and trust. These results suggest that
the emerging view of Grit as a facet of Conscientiousness is rather premature.
Further, we have shown that the facets of Grit do not predict life outcomes equally well.
The associations of Grit with all the subjective outcomes are driven mainly by the
Perseverance of effort facet, while it is the Consistency of interest facet that is related to educational
attainment. This last result contradicts the findings of
Credé et al. (2017
) who showed that
the Perseverance facet exhibits much stronger relations with academic performance. The
reason for this difference could be the nature of the educational outcomes analysed. While
Credé et al. (2017
) rely on grades, we look at the highest completed level of education.
Changing one’s interests often may not harm one’s grades, analysed as GPA counted across
subjects, but it may make it harder to complete a higher educational level.
This study is not without limitations. First, the cognitive skills were assessed around
three years earlier than personality traits and life outcomes which may result in weaker
associations than in reality. However, there is longitudinal evidence that cognitive skills
analysed are relatively stable over such a period or even fixed early in life
(Desjardins and
Warnke 2012)
.
Hill et al. (2008
) show that for school children, average annual gains in
literacy and numeracy decline with age and are already marginal by the age of 17. Second,
although the results presented describe relationships between personality traits and life
outcomes, drawing any conclusions about causality is not possible with the available data.
Bidirectional influences are likely to underlie the observed cross-sectional associations. This
is especially true for the analysis of educational attainment, as many respondents completed
their education many years before the personality traits were assessed and there is also
evidence that personality can be shaped by the educational system
(Dahmann and Anger
2014)
and tertiary education
(Kassenboehmer et al. 2018)
. We are aware that the lack of a
causal model is a serious limitation for designing policy interventions and for policy
analysis. Nevertheless, the analysis is of an exploratory nature and results stress the importance
of the topic, which might motivate further work on improving our understanding of the
mechanisms linking personality traits and life outcomes. Some authors show that
personality can change during one’s lifespan.
Specht et al. (2011
) conclude that the relationship of
personality with age is complex and curvilinear and can change due to the major life events.
To better understand to what degree personality may change over the lifespan and what
factors affect such changes we need more longitudinal studies on personality. Finally, the
relationships between personality traits and life outcomes are dynamic and complex.
Personality may influence life outcomes not only directly but also indirectly by contributing
to the development of cognitive skills and to the completion of educational qualifications.
Moreover, the analysed outcomes are also related with each other. We partially account
for indirect effects by controlling for educational attainment in all the models and for the
employment status in the social outcomes and life satisfaction models. However, examining
these relationships in one general model might be an avenue of future research.
The nature of personality traits differs from that of cognitive skills, such that “more”
does not necessarily mean “better”. From the policy-making perspective, the decision
which traits to foster may therefore be a difficult one. The value of incorporating
personality traits measures into international large-scale assessments would lie in the possibility
to compare the traits-outcome relationships between countries and groups within
countries, not in national rankings on personality traits. Some personality traits are beneficial
in some specific work environments but not in others. For example, Agreeableness is on
average related to lower wages but improves teamwork
(Tasa et al. 2011)
. A potential
solution would be to promote beneficial behaviours in specific contexts, e.g. being disagreeable
when negotiating wages but agreeable when working on a project involving teamwork.
Conclusion
In sum, given the potential benefits and relatively small burden on respondents in terms
of required time it seems advisable to incorporate measures of personality traits into
competence surveys as they contribute to explaining the variability in policy-relevant
outcomes. Taking into account the length of the scales analysed (eight and fifteen items
for Grit-S and BFI-S respectively), using the Big Five model seems preferable to using Grit
when a broad range of life outcomes is of interest, as the former covers multiple aspects
of personality. However, using both scales offers an improvement in explanatory power.
Additional files
Additional file 1. Literacy—full estimation results (OLS) Tables S1–S8.
Additional file 2. Numeracy—non-linear models Tables S1–S6.
Additional file 3. Numeracy—full estimation results (OLS) Tables S1–S8.
Authors’ contributions
MP originated the idea for the study, conducted the analyses and wrote the most of the manuscript. KŚ contributed to
the literature review. Both authors read and approved the final manuscript.
Author details
1 Educational Research Institute, Warsaw, Poland. 2 Warsaw School of Economics, Warsaw, Poland.
Acknowledgements
We thank Artur Pokropek, Michał Sitek, William Thorn and three anonymous referees for their insightful comments and
suggestions. We gratefully acknowledge financial support from the Organisation for Economic Co-operation and
Development (OECD). All errors are ours.
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
The postPIAAC dataset is administered by the Educational Research Institute in Warsaw and is not publicly available
online.
Ethics approval and consent to participate
Not applicable.
Funding
We thank the Organisation for Economic Co-operation and Development (OECD) for funding the analysis.
Appendix
See Tables 9, 10, 11, 12 and 13.
* p < 0.05, ** p < 0.01, *** p < 0.001. Dependent variable, numeracy and non‑ cognitive skills are standardised
Table 11 Self-declared labour force participation and cognitive and non-cognitive skills
(1) (2) (3) (4) (5) (6) (7)
Numeracy
Conscientiousness
Extraversion
Agreeableness
Openness
Neuroticism
Perseverance of effort
Consistency of interest
Age
Age # age
Female
Years of education
Constant
Observations
R2
Numeracy
Conscientiousness
Extraversion
Agreeableness
Openness
Neuroticism
Perseverance of effort
Consistency of interest
Age
Age # age
Female
Years of education
Constant
Observations
R2
* p < 0.05, ** p < 0.01, *** p < 0.001. (1)—The unidimensional model of Grit. (2)—two‑factor model of Grit. Control variables:
age, age squared, gender, years of education (outcomes 1–7), 1‑ digit ISCO (outcomes 3, 4), employment status (outcomes
5–7), parents education (outcome 8). Dependent variables, numeracy and non‑ cognitive skills are standardised
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